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Record W2296545989 · doi:10.21273/hortsci.51.1.98

Consequences of Deficit Irrigation and Crop Load Reduction on Plant Water Relations, Yield, and Quality of ‘Ambrosia’ Apple

2016· article· en· W2296545989 on OpenAlexaff
D. Neilsen, Gerry Neilsen, Sunghee Guak

Bibliographic record

VenueHortScience · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsIrrigationCropThinningDeficit irrigationMalusAgronomyEvapotranspirationGrowing seasonTranspirationEnvironmental scienceWater contentHorticultureStomatal conductanceRootstockBiologyPhotosynthesisBotanyIrrigation managementEcology

Abstract

fetched live from OpenAlex

Uncertain water supplies resulting from changing climatic conditions in western North America led to this investigation of the role of crop load reduction in maintaining performance of high-density ‘Ambrosia’ apple ( Malus × domestica) on M.9 rootstock. A split-plot experimental design was imposed for three growing seasons (2007–09) with six replicates of four main plot irrigation treatments and three crop load subplots comprised of three trees. Four season-long irrigation (Irr) treatments were applied through 2 × 4 L·h −1 drip emitters per tree and included Irr1) control [100% evapotranspiration (ET) replacement], Irr2) 50% ET replacement, Irr3) 50% ET replacement to half the emitters, and Irr4) an increasingly severe treatment commencing at 50% ET replacement (once every 2 days) in 2007 and progressing to 25% and 18% ET replacement, 2008–09. Three target crop loads were established annually, 4–5 weeks after bloom as low (2.5, 3, and 3.75), medium (4.5, 6, and 7.5), and high (9, 12, and 15) fruit/cm 2 trunk cross-sectional area (TCSA) 2007–09, respectively, by hand thinning around 4 weeks after bloom. Volumetric soil moisture contents generally reflected the amount of water applied and ranged from 20% for control (Irr1) to <10% for Irr4. Both irrigation and crop load treatments affected midday stem water potential more than leaf photosynthesis and stomatal conductance ( g S ). By the 2nd and 3rd year stem potential values for irrigation treatments ranged from a maximum of −1.0 to −1.3 MPa for Irr1 to minimums ≤-2.0 MPa for Irr4. g S decreased as midday stem potential decreased, but at any given stem potential value was greater at high crop loads, presumably in response to an increased demand for photosynthates. Fruit size decreased as crop load increased, but as irrigation deficits became more severe, fruit size was more closely correlated with stem water potential than g S . Consequently, fruit size was controlled by two mechanisms, competition for photosynthates and the effects of plant water status on g S . Negative linear relationships between crop load and average fruit size were used to determine the crop load required to produce an average fruit size of 200 g at different irrigation deficits. It was not possible to achieve adequate fruit size when applications were very low, as at 18% to 25% ET in Irr4. Crop load reduction around mid-June had no negative consequences for fruit quality, enhancing fruit color, and soluble solids concentration (SSC) and did not affect the incidence of sunburn, internal breakdown or bitter pit at harvest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.249
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2016
Admission routes1
Has abstractyes

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